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People are poorly equipped to detect AI-powered voice clones

  • arXiv (Cornell University)
  • Cornell University
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Abstract

As generative artificial intelligence (AI) continues its ballistic trajectory, everything from text to audio, image, and video generation continues to improve at mimicking human-generated content. Through a series of perceptual studies, we report on the realism of AI-generated voices in terms of identity matching and naturalness. We find human participants cannot consistently identify recordings of AI-generated voices. Specifically, participants perceived the identity of an AI-voice to be the same as its real counterpart approximately 80% of the time, and correctly identified a voice as AI generated only about 60% of the time.

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Publication details

DOI
10.48550/arxiv.2410.03791
OpenAlex
W4403322184
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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